Triple

T5854830
Position Surface form Disambiguated ID Type / Status
Subject Historic Centre of Vienna E130123 entity
Predicate hasLandmark P105 FINISHED
Object Kärntner Straße E348816 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kärntner Straße | Statement: [Historic Centre of Vienna, hasLandmark, Kärntner Straße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kärntner Straße
Context triple: [Historic Centre of Vienna, hasLandmark, Kärntner Straße]
  • A. Kärntner Straße chosen
    Kärntner Straße is one of Vienna’s most famous and busiest shopping streets, known for its pedestrian zone, historic architecture, and central location near major landmarks like St. Stephen’s Cathedral.
  • B. Seckbacher Landstraße
    Seckbacher Landstraße is a public transport stop in the Bornheim district of Frankfurt am Main, Germany.
  • C. Kochergasse
    Kochergasse is a central street in Bern, Switzerland, situated in the government district close to the Federal Palace and other key federal institutions.
  • D. Hofstallgasse
    Hofstallgasse is a historic street in Salzburg, Austria, known for housing major cultural landmarks including the Großes Festspielhaus of the Salzburg Festival.
  • E. Georgstraße
    Georgstraße is a major shopping and promenade street in the central district of Hanover, Germany, known for its retail stores, historic buildings, and cultural venues.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c0084de39081909eb34e6bed74215a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03554651c8190b3009d41eecf6779 completed March 22, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c107f608c48190b613741bf2686af7 completed March 23, 2026, 9:29 a.m.
Created at: March 22, 2026, 3:55 p.m.